Beyond cognitive ability: Susceptibility to fake news is also explained by associative inference

Sian Lee, Joshua P. Forrest, Jessica Strait, Haeseung Seo, Dongwon Lee, Aiping Xiong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations


We conducted a preliminary online study (N=261) investigating whether people's susceptibility to fake news on social media depends on how fake news are associated with real news that they viewed previously, as well as individuals' cognitive ability. Across two phases, we varied the association in three between-subjects conditions, i.e., associative inference, repetition, and irrelevant (control). Our study results showed limited impact of association type on participants of low cognitive ability. In contrast, for participants of high cognitive ability, their discrimination of fake news from real news tended to be worse for the associative inference condition than for the other two conditions. Thus, our findings suggest that individuals of high cognitive ability are likely to be susceptible to form the belief of fake news, but differently from those of low cognitive ability.

Original languageEnglish (US)
Title of host publicationCHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450368193
StatePublished - Apr 25 2020
Event2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020 - Honolulu, United States
Duration: Apr 25 2020Apr 30 2020

Publication series

NameConference on Human Factors in Computing Systems - Proceedings


Conference2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

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